231,466 research outputs found
CyberLiveApp: a secure sharing and migration approach for live virtual desktop applications in a cloud environment
In recent years we have witnessed the rapid advent of cloud computing, in which the remote software is delivered as a service and accessed by users using a thin client over the Internet. In particular, the traditional desktop application can execute in the remote virtual machines without re-architecture providing a personal desktop experience to users through remote display technologies. However, existing cloud desktop applications mainly achieve isolation environments using virtual machines (VMs), which cannot adequately support application-oriented collaborations between multiple users and VMs. In this paper, we propose a flexible collaboration approach, named CyberLiveApp, to enable live virtual desktop applications sharing based on a cloud and virtualization infrastructure. The CyberLiveApp supports secure application sharing and on-demand migration among multiple users or equipment. To support VM desktop sharing among multiple users, a secure access mechanism is developed to distinguish view privileges allowing window operation events to be tracked to compute hidden window areas in real time. A proxy-based window filtering mechanism is also proposed to deliver desktops to different users. To support application sharing and migration between VMs, we use the presentation streaming redirection mechanism and VM cloning service. These approaches have been preliminary evaluated on an extended MetaVNC. Results of evaluations have verified that these approaches are effective and useful
Advanced Cloud Privacy Threat Modeling
Privacy-preservation for sensitive data has become a challenging issue in
cloud computing. Threat modeling as a part of requirements engineering in
secure software development provides a structured approach for identifying
attacks and proposing countermeasures against the exploitation of
vulnerabilities in a system . This paper describes an extension of Cloud
Privacy Threat Modeling (CPTM) methodology for privacy threat modeling in
relation to processing sensitive data in cloud computing environments. It
describes the modeling methodology that involved applying Method Engineering to
specify characteristics of a cloud privacy threat modeling methodology,
different steps in the proposed methodology and corresponding products. We
believe that the extended methodology facilitates the application of a
privacy-preserving cloud software development approach from requirements
engineering to design
Enabling Interactive Analytics of Secure Data using Cloud Kotta
Research, especially in the social sciences and humanities, is increasingly
reliant on the application of data science methods to analyze large amounts of
(often private) data. Secure data enclaves provide a solution for managing and
analyzing private data. However, such enclaves do not readily support discovery
science---a form of exploratory or interactive analysis by which researchers
execute a range of (sometimes large) analyses in an iterative and collaborative
manner. The batch computing model offered by many data enclaves is well suited
to executing large compute tasks; however it is far from ideal for day-to-day
discovery science. As researchers must submit jobs to queues and wait for
results, the high latencies inherent in queue-based, batch computing systems
hinder interactive analysis. In this paper we describe how we have augmented
the Cloud Kotta secure data enclave to support collaborative and interactive
analysis of sensitive data. Our model uses Jupyter notebooks as a flexible
analysis environment and Python language constructs to support the execution of
arbitrary functions on private data within this secure framework.Comment: To appear in Proceedings of Workshop on Scientific Cloud Computing,
Washington, DC USA, June 2017 (ScienceCloud 2017), 7 page
Trusted integration of cloud-based NFC transaction players
Near Field Communication (NFC) is a short range wireless technology that provides contactless transmission of data between devices. With an NFC enabled device, users can exchange information from one device to another, make payments and use their NFC enabled device as their identity. As the main payment ecosystem players such as service providers and secure element issuers have crucial roles in a multi-application mobile environment similar to NFC, managing such an environment has become very challenging. One of the technologies that can be used to ensure secure NFC transaction is cloud computing which offers wide range of advantages compare to the use of a Secure Element (SE) as a single entity in an NFC enabled phone. This approach provides a comprehensive leadership of the cloud provider towards managing and controlling customer's information where it allows the SE which is stored within an NFC phone to deal with authentication mechanisms rather than storing and managing sensitive transaction information. This paper discusses the NFC cloud Wallet model which has been proposed by us previously [1] and introduces a different insight that defines a new integrated framework based on a trusted relationship between the vendor and the Mobile Network Operator (MNO). We then carry out an analysis of such a relationship to investigate different possibilities that arise from this approach
Secure multi-party computation for analytics deployed as a lightweight web application
We describe the definition, design, implementation, and deployment of a secure multi-party computation protocol and web application. The protocol and application allow groups of cooperating parties with minimal expertise and no specialized resources to compute basic statistical analytics on their collective data sets without revealing the contributions of individual participants. The application was developed specifically to support a Boston Women’s Workforce Council (BWWC) study of wage disparities within employer organizations in the Greater Boston Area. The application has been deployed successfully to support two data collection sessions (in 2015 and in 2016) to obtain data pertaining to compensation levels across genders and demographics. Our experience provides insights into the particular security and usability requirements (and tradeoffs) a successful “MPC-as-a-service” platform design and implementation must negotiate.We would like to acknowledge all the members of the Boston Women’s Workforce Council, and to thank in particular MaryRose Mazzola, Christina M. Knowles, and Katie A. Johnston, who led the efforts to organize participants and deploy the protocol as part of the 100% Talent: The Boston Women’s Compact [31], [32] data collections. We also thank the Boston University Initiative on Cities (IOC), and in particular Executive Director Katherine Lusk, who brought this potential application of secure multi-party computation to our attention. The BWWC, the IOC, and several sponsors contributed funding to complete this work. Support was also provided in part by Smart-city Cloud-based Open Platform and Ecosystem (SCOPE), an NSF Division of Industrial Innovation and Partnerships PFI:BIC project under award #1430145, and by Modular Approach to Cloud Security (MACS), an NSF CISE CNS SaTC Frontier project under award #1414119
Usługi biblioteczne w dobie cloud computing – technologia, dane, sieciowe, społeczności informacyjne
This text refer s to the application of cloud computing technology in modern libraries, with particular emphasis on large academic institutions. Based on the experiences of the Library of Congress, benefits from the use of cloud services by libraries and recommendations for the secure use of cloud technology. Networking of cloud-based information communities contributes to the growth of book and reader promotion, library support, and book development
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